code: def get_local_maximum(heat, kernel=3):
      """Extract local maximum pixel with given kernel.
  
      Args:
          heat (Tensor): Target heatmap.
          kernel (int): Kernel size of max pooling. Default: 3.
  
      Returns:
          heat (Tensor): A heatmap where local maximum pixels maintain its
              own value and other positions are 0.
      """
      pad = (kernel - 1) // 2
      hmax = F.max_pool2d(heat, kernel, stride=1, padding=pad)
      keep = (hmax == heat).float()
      return heat * keep
  
file_path: mmdetection/mmdet/models/utils/gaussian_target.py
imports: from math import sqrt
  import torch
  import torch.nn.functional
label_desc: Use image node_id 4 for calling a global function with example usage: get_local_maximum(heat, kernel) and returns: unknown